@inproceedings{12584b35c9c4462a93ff67a8acd8d4cf,
title = "TopoText: Context-preserving Text data exploration across multiple spatial scales",
abstract = "TopoText is a context-preserving technique for visualizing text data for multi-scale spatial aggregates to gain insight into spatial phenomena. Conventional exploration requires users to navigate across multiple scales but only presents the information related to the current scale. This limitation potentially adds more steps of interaction and cognitive overload to the users. TopoText renders multi-scale aggregates into a single visual display combining novel text-based encoding and layout methods that draw labels along the boundary or filled within the aggregates. The text itself not only summarizes the semantics at each individual scale, but also indicates the spatial coverage of the aggregates and their underlying hierarchical relationships. We validate TopoText with both a user study as well as several application examples.",
keywords = "Context preservation, Geospatial visualization, Multi-scale analysi, Text visualization, Typographic map",
author = "Jiawei Zhang and Chittayong Surakitbanharn and Niklas Elmqvist and Ross Maciejewski and Zhenyu Qian and Ebert, {David S.}",
note = "Publisher Copyright: {\textcopyright} 2018 ACM.; 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018 ; Conference date: 21-04-2018 Through 26-04-2018",
year = "2018",
month = apr,
day = "20",
doi = "10.1145/3173574.3173611",
language = "English (US)",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
booktitle = "CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems",
}